SoroushVahidi/scidocs huggingface dataset:
Incremental Task and Motion Planning: A Constraint-Based Approach
(2016)

We present a new algorithm for task and motion planning (TMP) and discuss the requirements and abstractions necessary to obtain robust solutions for TMP in general. Our Iteratively Deepened Task and Motion Planning (IDTMP) method is probabilistically-complete and offers improved performance and generality compared to a similar, state-of-theart, probabilistically-complete planner. The key idea of IDTMP is to leverage incremental constraint solving to efficiently add and remove constraints on motion feasibility at the task level. We validate IDTMP on a physical manipulator and evaluate scalability on scenarios with many objects and long plans, showing order-of-magnitude gains compared to the benchmark planner and a four-times self-comparison speedup from our extensions. Finally, in addition to describing a new method for TMP and its implementation on a physical robot, we also put forward requirements and abstractions for the development of similar planners in the future.
David J. Chalmers The Singularity A Philosophical Analysis
(2010)

What happens when machines become more intelligent than humans? One view is that this event will be followed by an explosion to evergreater levels of intelligence, as each generation of machines creates more intelligent machines in turn. This intelligence explosion is now often known as the ‘singularity’. The basic argument here was set out by the statistician I.J. Good in his 1965 article ‘Speculations Concerning the First Ultraintelligent Machine’:
Comparing Entities in RDF Graphs
(2017)

The Semantic Web has fuelled the appearance of numerous open-source knowledge bases. Knowledge bases enable new types of information search, going beyond classical query answering and into the realm of exploratory search, and providing answers to new types of user questions. One such question is how two entities are comparable, i.e., what are similarities and differences between the information known about the two entities. Entity comparison is an important task and a widely used functionality available in many information systems. Yet it is usually domain-specific and depends on a fixed set of aspects to compare. In this paper we propose a formal framework for domain-independent entity comparison that provides similarity and difference explanations for input entities. We model explanations as conjunctive queries, we discuss how multiple explanations for an entity pair can be ranked and we provide a polynomial-time algorithm for generating most specific similarity explanations.
A meta-analytic review of the effects of acute cortisol administration on human memory
(2005)

Adrenal glucocorticoids (GC) secreted during stress modulate memory. Animal and human studies investigating the effects of acute GC treatment on memory have reported conflicting (enhancing as well as impairing) results. Several theories have been proposed to integrate these contradictory findings. Among the variables discussed are the timing of the GC treatment (before learning or before retrieval) and the time of day (morning versus afternoon). Here we review meta-analytically the results of 16 studies, which experimentally investigated the acute impact of cortisol treatment on human memory. The results revealed that the timing of GC application in the course of a study is a relevant variable which explains a substantial amount of the significant heterogeneity within the effect sizes. The studies which administered cortisol before retrieval (n = 4) reported a significant decrease (average effect size of d = -.49) in memory performance. Studies which administered cortisol before learning (n =12) found on average no effect (d = .08), but there is heterogeneity within these effect sizes. Further analysis on these experiments indicated that studies, which administered cortisol in the morning found a significant memory impairment (d = -.40), while studies conducted in the afternoon observed a small but significant memory enhancement (d = .22). This meta-analysis supports the idea that the timing of GC administration (before learning or before retrieval) is a major determinant of the effects of GCs on human memory. We discuss methodological limitations of the current analysis and suggest several areas for future research.
Collaborative Edge and Cloud Neural Networks for Real-Time Video Processing
(2018)

The efficient processing of video streams is a key component in many emerging Internet of Things (IoT) and edge applications, such as Virtual and Augmented Reality (V/AR) and self-driving cars. These applications require real-time high-throughput video processing. This can be attained via a collaborative processing model between the edge and the cloud—called an Edge-Cloud model. To this end, many approaches were proposed to optimize the latency and bandwidth consumption of Edge-Cloud video processing, especially for Neural Networks (NN)-based methods. In this demonstration. We investigate the efficiency of these NN techniques, how they can be combined, and whether combining them leads to better performance. Our demonstration invites participants to experiment with the various NN techniques, combine them, and observe how the underlying NN changes with different techniques and how these changes affect accuracy, latency and bandwidth consumption. PVLDB Reference Format: Philipp M. Grulich and Faisal Nawab. Collaborative Edge and Cloud Neural Networks for Real-Time Video Processing. PVLDB, 11 (12): 2046-2049, 2018. DOI: https://doi.org/10.14778/3229863.3236256
Measuring Motivations of Crowdworkers: The Multidimensional Crowdworker Motivation Scale
(2017)

Crowd employment is a new form of short term and flexible employment which has emerged during the past decade. For understanding this new form of employment, it is crucial to understand the underlying motivations of the workforce involved in it. This paper presents the Multidimensional Crowdworker Motivation Scale (MCMS), a scale for measuring the motivation of crowdworkers on micro-task platforms. The scale is theoretically grounded in Self-Determination Theory and tailored specifically to the context of crowdsourced micro-labor. The MCMS was validated on data collected in ten countries and three income groups. Furthermore, measurement invariance tests showed that motivations measured with the MCMS are comparable across countries and income groups. This work constitutes a first step towards understanding the motivations of the international crowd workforce.
High-Performance Distributed ML at Scale through Parameter Server Consistency Models
(2015)

As Machine Learning (ML) applications embrace greater data size and model complexity, practitioners turn to distributed clusters to satisfy the increased computational and memory demands. Effective use of clusters for ML programs requires considerable expertise in writing distributed code, but existing highlyabstracted frameworks like Hadoop that pose low bar-ed frameworks like Hadoop that pose low barriers to distributed-programming have not, in practice, matched the performance seen in highly specialized and advanced ML implementations. The recent Parameter Server (PS) paradigm is a middle ground between these extremes, allowing easy conversion of single-machine parallel ML programs into distributed ones, while maintaining high throughput through relaxed “consistency models” that allow asynchronous (and, hence, inconsistent) parameter reads. However, due to insufficient theoretical study, it is not clear which of these consistency models can really ensure correct ML algorithm output; at the same time, there remain many theoreticallymotivated but undiscovered opportunities to maximize computational throughput. Inspired by this challenge, we study both the theoretical guarantees and empirical behavior of iterative-convergent ML algorithms in existing PS consistency models. We then use the gleaned insights to improve a consistency model using an “eager” PS communication mechanism, and implement it as a new PS system that enables ML programs to reach their solution more quickly.
Vision-Controlled Micro Flying Robots: From System Design to Autonomous Navigation and Mapping in GPS-Denied Environments
(2014)

Autonomous microhelicopters will soon play a major role in tasks like search and rescue, environment monitoring, security surveillance, and inspection. If they are further realized in small scale, they can also be used in narrow outdoor and indoor environments and represent only a limited risk for people. However, for such operations, navigating based only on global positioning system (GPS) information is not sufficient. Fully autonomous operation in cities or other dense environments requires microhelicopters to fly at low altitudes, where GPS signals are often shadowed, or indoors and to actively explore unknown environments while avoiding collisions and creating maps. This involves a number of challenges on all levels of helicopter design, perception, actuation, control, and navigation, which still have to be solved. The Swarm of Micro Flying Robots (SFLY) project was a European Union-funded project with the goal of creating a swarm of vision-controlled microaerial vehicles (MAVs) capable of autonomous navigation, three-dimensional (3-D) mapping, and optimal surveillance coverage in GPS-denied environments. The SFLY MAVs do not rely on remote control, radio beacons, or motion-capture systems but can fly all by themselves using only a single onboard camera and an inertial measurement unit (IMU). This article describes the technical challenges that have been faced and the results achieved from hardware design and embedded programming to vision-based navigation and mapping, with an overview of how all the modules work and how they have been integrated into the final system. Code, data sets, and videos are publicly available to the robotics community. Experimental results demonstrating three MAVs navigating autonomously in an unknown GPS-denied environment and performing 3-D mapping and optimal surveillance coverage are presented.
Minimum snap trajectory generation and control for quadrotors
(2011)

We address the controller design and the trajectory generation for a quadrotor maneuvering in three dimensions in a tightly constrained setting typical of indoor environments. In such settings, it is necessary to allow for significant excursions of the attitude from the hover state and small angle approximations cannot be justified for the roll and pitch. We develop an algorithm that enables the real-time generation of optimal trajectories through a sequence of 3-D positions and yaw angles, while ensuring safe passage through specified corridors and satisfying constraints on velocities, accelerations and inputs. A nonlinear controller ensures the faithful tracking of these trajectories. Experimental results illustrate the application of the method to fast motion (5–10 body lengths/second) in three-dimensional slalom courses.
Autonomous indoor 3D exploration with a micro-aerial vehicle
(2012)

In this paper, we propose a stochastic differential equation-based exploration algorithm to enable exploration in three-dimensional indoor environments with a payload constrained micro-aerial vehicle (MAV). We are able to address computation, memory, and sensor limitations by considering only the known occupied space in the current map. We determine regions for further exploration based on the evolution of a stochastic differential equation that simulates the expansion of a system of particles with Newtonian dynamics. The regions of most significant particle expansion correlate to unexplored space. After identifying and processing these regions, the autonomous MAV navigates to these locations to enable fully autonomous exploration. The performance of the approach is demonstrated through numerical simulations and experimental results in single and multi-floor indoor experiments.
A (Very) Brief History of Artificial Intelligence
(2005)

telligence are traced to philosophy, fiction, and imagination. Early inventions in electronics, engineering, and many other disciplines have influenced AI. Some early milestones include work in problems solving which included basic work in learning, knowledge representation, and inference as well as demonstration programs in language understanding, translation, theorem proving, associative memory, and knowledge-based systems. The article ends with a brief examination of influential organizations and current issues facing the field.
Culture and Conformity : A Meta-Analysis of Studies Using Asch ' s ( 1952 b , 1956 ) Line Judgment Task
(1996)

A meta-analysis of conformity studies using an Asch-type line judgment task (1952b, 1956) was conducted to investigate whether the level of conformity has changed over time and whether it is related crogs-culturally to individualism-collectivism. The fiterature search produced 133 studies drawn from 17 countries. An analysis of U.S. studies found that conformity has declined since the 1950s. Results from 3 surveys were used to assess a country's individualism-collectivism, and for each survey the measures were found to be significantly related to conformity. Collectivist countries tended to show higher levels of conformity than individualist countries. Conformity research must attend more to cultural variables and to their role in the processes involved in social influence.
Generative Single Image Reflection Separation
(2018)

Single image reflection separation is an ill-posed problem since two scenes, a transmitted scene and a reflected scene, need to be inferred from a single observation. To make the problem tractable, in this work we assume that categories of two scenes are known. It allows us to address the problem by generating both scenes that belong to the categories while their contents are constrained to match with the observed image. A novel network architecture is proposed to render realistic images of both scenes based on adversarial learning. The network can be trained in a weakly supervised manner, i.e., it learns to separate an observed image without corresponding ground truth images of transmission and reflection scenes which are difficult to collect in practice. Experimental results on real and synthetic datasets demonstrate that the proposed algorithm performs favorably against existing methods.
UAVS FOR THE DOCUMENTATION OF ARCHAEOLOGICAL EXCAVATIONS
(2010)

UAV photogrammetry experienced a growing variety of diverse applications in different scientific disciplines. Comparable early, UAVs were deployed in the Cultural Heritage and Archaeology domains, mainly for the purpose of monument, building and landscape modelling. In this paper, we will focus on the investigation of UAV application for documenting archaeological excavations. Due to the fact, that excavations are dynamic processes and therefore the objects to be acquired change significantly within few hours, UAVs can provide a suitable alternative to traditional measurement methods such as measuring tape and tachymeter in some cases. Nevertheless, the image processing steps have to be automated to a large amount as results, usually sketches, maps, orthophotos and 3D models, should be available temporally close to the related excavation event. In order to accelerate the processing workflow, an interface between the UAV ground control software and various photogrammetric software packages was developed at ETH Zurich which allows for an efficient management and transfer of orientation, trajectory and sensor data for fast project setup. The capabilities of photogrammetric methods using UAVs as a sensor platform will be demonstrated in 3 case studies: The documentation of a large archaeological site in Bhutan, an excavation of a smaller site containing ancient tombs which include several uncovered objects in the Nasca region in Peru and the Maya site of Copán in Honduras. The first and the third case study deal with the 3D modelling of buildings and their remains by means of photogrammetry, which means that accurate flight planning had to be applied and followed during the flights. In the second case study, we acquired various aerial images over the excavation area Pernil Alto near Palpa in a more simple way for quick documentation of the area of interest. In a third part, we will present our results from comparisons between the planned positions for image acquisition and the positions realized by the navigation unit during the flight for both UAV systems mentioned above. We will describe how accurate orientation data improve automated image processing if they are at hand directly after the flight and explain the workflow developed at ETH Zurich.
Reversible Alopecia with Localized Scalp Necrosis After Accidental Embolization of the Parietal Artery with Hyaluronic Acid
(2017)

Hyaluronic acid (HA) filler injection is widely used for soft-tissue augmentation. Complications associated with HA filling are not uncommon; however, HA-induced alopecia is a rarely reported complication that could result in severe secondary psychological trauma. The etiology, clinical traits, treatment strategies, outcomes, and possible reversibility of HA-induced alopecia have not been characterized. Here, we report a case in which bilateral temple injections of 6.5 mL of HA led to persistent pain over the left scalp for several days. Although the pain was relieved at day 9 after 600 U of hyaluronidase were injected in the left temple, the patient developed localized alopecia at the left temporoparietal region with central skin necrosis at day 15. After topical applications of recombinant bovine basic fibroblast growth factor gel and 2% minoxidil spay, the necrotic skin wound was healed at day 42. Hair regrowth and normal hair density were restored at day 74. Analyses of Doppler ultrasound examinations and histopathology of the skin biopsy suggested that mild ischemia of the left temporoparietal region led to reversible alopecia, while the permanent hair loss in the left parietal area was associated with severe skin ischemia. Therefore, the key to treatment would be to focus on the effective correction of severe ischemia-induced skin necrosis to prevent permanent hair loss. Level of Evidence V This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
A Survey of Homomorphic Encryption for Nonspecialists
(2007)

The goal of encryption is to ensure confidentiali y of data in communication and storage processes. Recently, its use in constrained devices led to consider additional features, such as the ability to delegate computations to untrusted computers. For this purpose, we would like to give the untrusted computer only an encrypted version of the data to process. The computer will perform the computation on this encrypted data, hence without knowing anything on its real value. Finally, it will send back the result, and we will decrypt it. For coherence, the decrypted result has to be equal to the intended computed value if performed on the original data. For this reason, the encryption scheme has to present a particular structure. Rivest et al. proposed in 1978 to solve this issue through homomorphic encryption [1]. Unfortunately, Brickell and Yacobi pointed out in [2] some security f aws in the firs proposals of Rivest et al. Since this f rst attempt, a lot of articles have proposed solutions dedicated to numerous application contexts: secret sharing schemes, threshold schemes (see, e.g., [3]), zero-knowledge proofs (see, e.g., [4]), oblivious transfer (see, e.g., [5]), commitment schemes (see, e.g., [3]), anonymity, privacy, electronic voting, electronic auctions, lottery protocols (see, e.g., [6]), protection ofmobile agents (see, e.g., [7]), multiparty computation (see, e.g., [3]), mix-nets (see, e.g., [8, 9]), watermarking or finge printing protocols (see, e.g., [10–14]), and so forth. The goal of this article is to provide nonspecialists with a survey of homomorphic encryption techniques. Section 2 recalls some basic concepts of cryptography and presents homomorphic encryption; it is particularly aimed at noncryptographers, providing guidelines about the main characteristics of encryption primitives: algorithms, performance, security. Section 3 provides a survey of homomorphic encryption schemes published so far, and analyses their characteristics. Most schemes we describe are based onmathematical notions the reader may not be familiar with. In the cases these notions can easily be introduced, we present them briefl . The reader may refer to [15] for more information concerning those we could not introduce properly, or algorithmic problems related to their computation. Before going deeper in the subject, let us introduce some notation. The integer (x) denotes the number of bits constituting the binary expansion of x. As usual, Zn will denote the set of integers modulo n, and Z∗n the set of its invertible elements.
4W1H in mobile crowd sensing
(2014)

With the rapid proliferation of sensor-rich smartphones, mobile crowd sensing has become a popular research field. In this article, we propose a four-stage life cycle (i.e., task creation, task assignment, individual task execution, and crowd data integration) to characterize the mobile crowd sensing process, and use 4W1H (i.e., what, when, where, who, and how) to sort out the research problems in the mobile crowd sensing domain. Furthermore, we attempt to foresee some new research directions in future mobile crowd sensing research.
Assistive, Rehabilitation, and Surgical Robots from the Perspective of Medical and Healthcare Professionals
(2007)

The presence of robots in the medical and healthcare fields is increasing. Commercially available medical and healthcare robots are in use by hospitals and nursing homes. Many more assistive, rehabilitation, and surgical robots are being developed at research institutions. In this paper, we examine the awareness of medical and healthcare professionals with respect to robotic applications and the social and psychological impacts of human-robot interaction.
Computer-aided organic synthesis.
(2005)

It is tempting for those in the field of organic synthesis to liken the process of retrosynthesis to a game of chess. That the world chess champion was recently defeated by a computer leads us to think that perhaps new and powerful computing methods could be applied to synthetic problems. Here the analogy between synthesis and chess is outlined. Achievements in the 35-year history of computer-aided synthetic design are described, followed by some more recent developments.
Finline Ortho-Mode Transducer for Millimeter Waves
(1999)

We evaluate the possibility of using a finline orthomode transducer (OMT) at millimeter wavelengths. A finline OMT has low loss, low cross-polarization, and good return loss over a full waveguide band. We propose a novel finline OMT structure for millimeter-wavelengths and present results at X-band.
A novel broadband EBG using multi-period mushroom-like structure
(2008)

A novel broadband electromagnetic band-gap (EBG) structure is presented using multi-period mushroom-like structure with different patch size cascaded. Direct transmission method is used to determine the band-gap of the EBG structure. The effects of the unit number and patch size on the mushroomlike EBG structure are investigated. Two kinds of unit with different patch size are cascaded to enlarge the band-gap of EBG structure, which achieves almost 87.1%. The simulation results show that the band-gap almost covers the stop-band produced by the two uniform configurations with different patch size respectively.